Summary: Multiphoton microscopy (MPM) is a nonlinear laser scanning microscopy technique that features high three-dimensional resolution, fast imaging capabilities and label-free molecular contrast. Several endogenous tissue components can be visualized, including collagen (through second-harmonic generation, SHG), reduced nicotinamide adenine dinucleotide (NADH), flavin adenosine dinucleotide (FAD), keratin, melanin and elastin fibers (through two-photon excited fluorescence, TPEF). The ability to generate high- resolution images of tissue structure and composition without the need for exogenous labels makes MPM imaging particularly well-suited for characterizing superficial tissues in vivo. The purpose of this clinical imaging proposal is to evaluate the ability of in viv multiphoton microscopy to provide quantitative optical endpoints with sufficiently high predictive power to reliably distinguish between pigmented lesions in three groups: common nevi, atypical nevi and melanoma. The framework is based on our preliminary results obtained from a 15-lesion (14 patient) study where we identified three optical biomarkers related to TPEF and SHG signals and correlated these in vivo molecular features with conventional ex vivo histopathologic criteria. MPM biomarkers were combined to obtain a quantitative, 9-point numerical index (multi-photon melanoma index, MMI) that distinguished between common nevi (MMI = 0-1), atypical nevi (MMI = 1-4) and melanoma (MMI = 5-8) (p<0.05). We now propose a powered prospective clinical trial that follows on these promising results in order to determine whether the MMI, or similar MPM-derived index, can be reliably used in a clinical setting. We expect our results will provide a validated decision-making endpoint to increase clinical diagnosis accuracy of common nevi, atypical nevi and melanoma. In addition, our effort to correlate in vivo MPM-derived contrast with conventional histopathology is expected to lead to new insight regarding the origins of melanoma appearance and progression. Our long-term goal is to identify the right combination of quantitative clinical endpoints that would improve clinical diagnoses, guide effective treatment, and eliminate unnecessary biopsies while increasing identification of lesions requiring removal.